Do you ever feel like you’re being watched? Do you feel like your phone or your laptop is listening to you? Very likely, it is, and belongs to a new class of software that is trained to observe your behavior and predict your desires, or at least to correctly guess what you’ll type next. This kind of software has become increasingly common: it is embedded into the websites we visit such as the search algorithms in Google, Netflix, and Amazon; listening to us through Siri, Alexa, Cortana, and Google Assistant; watching us through cameras in our personal technologies and in our cities leading to facial recognition, Snapchat filters, and “deepfakes.” Generative media is not just a tool that we use, but an increasingly active collaborator with us across media forms in our everyday lives. This course will explore the emerging field of generative media through a series of case studies ranging from visual and social media, digital technology and coding, audio recognition and synthesis, and the intersections of contemporary art practices and data science. We will draw on ideas from machine learning and artificial intelligence, digital theory and the history of technology, and philosophy to consider questions about the evolution of AI such as: is it possible for an AI to become fully conscious and autonomous? What is happening when my phone responds to a question? Can a computer make art? What does the phenomenology of artificial intelligence look like? What would it mean for an AI to have its own style or aesthetic? We will begin to answer these questions through an exploration generative media from the perspective of media studies, computer science and cybernetics, neural networks and deep learning, and generative adversarial networks. This course will emphasize philosophical, historical, and theoretical understandings of artificial intelligence and machine learning while looking to a diverse array of examples from contemporary art, digital culture, and popular media. [Tracks C, M]